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NASA MERRA

The Modern Era Retrospective-Analysis for Research and Applications (MERRA) was undertaken by NASA’s Global Modeling and Assimilation Office with two primary objectives: to place observations from NASA’s Earth Observing System satellites into a climate context and to improve upon the hydrologic cycle represented in earlier generations of reanalyses. MERRA was generated with version 5.2.0 of the Goddard Earth Observing System (GEOS) atmospheric model and data assimilation system (DAS), and covers the modern satellite era from 1979 to the present. Specifically, the GEOS-DAS Version 5 implements Incremental Analysis Updates (IAU) to slowly adjust the model states toward the observed state.

The original MERRA has been replaced by MERRA-2.

Key Strengths:

Significant improvement in precipitation and water vapor climatology over older reanalyses

The IAU procedure in which the analysis correction is applied to the forecast model gradually ameliorates precipitation spin-down during early stages of the forecast, and allows for higher frequency output including selected hourly fields

Provides vertical integrals and analysis increment fields for the closure of atmospheric budgets

Key Limitations:

Changes in the observing system strongly affect trends in many fields (as for other reanalyses); for example P-E exhibits spurious increases associated with assimilating radiances from the AMSU starting in 1998 and to a lesser extent, SSM/I in 1987

The assimilation routine is “frozen” and will not be updated for newer satellite instruments, so quality will eventually degrade as current instruments expire

Expert Developer Guidance

The summary information was written with help from Richard Cullather. Any errors are ours.

Technical Notes

MERRA FAQ 6: Why are there such large discrepancies at 1000mb and 850mb bewtween MERRA and other reanalyses?

The GEOS5 data assimilation system used to produce MERRA does not (or did not at the time of production) extrapolate data to pressure levels greater than the surface pressure. These grid points are marked by undefined values. The result is that area averages that include these points will not be representative compared to other data sets without additional screening. Time averages, such as monthly means, may also have substantial differences at the edges of topography. The lowest model level data and surface data are available so that users can produce their own extrapolation. A page discussing this issue is available. See http://gmao.gsfc.nasa.gov/research/merra/pressure_surface.php

Key Figures

Click the thumbnails to view larger sizes

Thumbnails

Captions

Taylor diagrams of annual mean precipitation from reanalyses using GPCP and CMAP as observing references. Red and blue lines show limits of expected high and low correlation determined by comparing GPCP and CMAP. From Bosilovich et al. (2011) and contributed by R. Cullather.

Climatological (1989-2010) total water vapor for January and July. [Climate Data Guide; D. Shea]

Cite this page

Acknowledgement of any material taken from this page is appreciated. On behalf of experts who have contributed data, advice, and/or figures, please cite their work as well.

NASA MERRA

The Modern Era Retrospective-Analysis for Research and Applications (MERRA) was undertaken by NASA’s Global Modeling and Assimilation Office with two primary objectives: to place observations from NASA’s Earth Observing System satellites into a climate context and to improve upon the hydrologic cycle represented in earlier generations of reanalyses. MERRA was generated with version 5.2.0 of the Goddard Earth Observing System (GEOS) atmospheric model and data assimilation system (DAS), and covers the modern satellite era from 1979 to the present. Specifically, the GEOS-DAS Version 5 implements Incremental Analysis Updates (IAU) to slowly adjust the model states toward the observed state.
The original MERRA has been replaced by MERRA-2.

The National Center for Atmospheric Research is sponsored by the National Science Foundation. Any opinions, findings and conclusions or recommendations expressed in this material do not necessarily reflect the views of the National Science Foundation.